Advancements in digital communication technologies have permitted the development and deployment of digital communication systems capable of communicating, and operating upon, large amounts of data. Data-intensive communication services, previously wholly unavailable or impracticably cost-prohibitive, are now available to large segments of the population. And, additional, even more, data-intensive communication services are likely to be provided in the future.
Digital radio communication systems are amongst the communication systems that have taken advantage of the advancements in digital communication techniques. A cellular radio communication system is an exemplary type of radio communication system. Use of a cellular communication system through which to communicate is pervasive in many parts of the populated areas of the world. While early-generation cellular communication systems were used primarily for voice communication services, new-generation systems are increasingly used for data-intensive, data communication services, such as multimedia communication services.
A cellular communication system is a bandwidth-constrained system. Other radio communication systems are typically also bandwidth-constrained. The radio-frequency bandwidth allocated to a cellular communication system is limited. And, due to the limited allocation, the communication capacity of the system is constrained. Significant efforts have been made to make efficient use of the bandwidth allocated for use in a cellular, or other bandwidth-constrained, communication system. And, as the communication channels upon which data is communicated are typically non-ideal, susceptible, e.g., to fading, noise, and other interference and distortion, significant efforts have also been made to compensate for, or otherwise overcome, the impairment introduced upon the data as a result of its communication upon non-ideal channels.
Recent research in wireless communications has proven that the channel capacity in fading environment can be greatly increased by exploiting the spatial diversity by using multiple transmit antennas, multiple receive antennas, or both multiple transmit and receive antennas. In communication systems with multiple antennas, the message-carrying data needs to be properly encoded in both spatial and temporal dimensions, resulting in the so-called space-time code (STC). Among many STC techniques, space-time block code (STBC) is one of the most popular one, in which the data are coded in blocks.
With increased channel capacity through STBC with multiple antennas, data can be transmitted with reduced error rate, or at an increased data rate, or with both improvements. However, decoding of the coded data with STBC requires increased computational complexity at a receiving communication station. In principle, the optimum error-rate performance is achievable by using maximum likelihood detection, however the computational complexity makes it impractical to use in reality in most applications. Spherical detection, such as that carried out by a sphere detector (SD) provides optimal detection with reduced computational complexity, but still requires significant computing complexity levels. The computational complexity required to recover the informational content of the data is particularly problematical when performed at a mobile station, or other communication station, that is of relatively low computational capability.
If a manner could be provided by which to make detection of a space-time block code requiring reduced computational complexity, the advantages provided by the use of a space-time block code would be provided without the corresponding disadvantages required of processing-intensive decoding techniques.
It is light of this background information related to the communication of data in a communication system that the significant improvements of the present invention have evolved.